Twitter users’ perception of AI in remote proctoring
Résumé
As a consequence of the COVID-19 pandemic, many educational institutions have turned to AI-based remote proctoring solutions to monitor students during online examinations. The deployment of such software has caused some concerns: reports of unfair treatment and accusations of racist and ableist systems have widely circu- lated in social media. Twitter has been at the forefront of these debates. The present study thus investigates how AI in online proctoring is portrayed by different stake- holders (e.g. companies, students, and representatives of educational institutions) in Twitter discourse. To this end, we compiled a small, highly specialised corpus of tweets (N = 467) which we manually tagged following a Qualitative Content Analy- sis (QCA) approach. The annotated data allows for the fine-grained analysis of the terminology used to describe AI in the context of remote proctoring in combination with the benefits, issues and emotions that Twitter users associate with such soft- ware. Our results suggest that general terms are preferred over more specialised ones. We also show that some terms are used inconsistently by the general public and sometimes even misleadingly by online proctoring companies themselves.
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